American Samoa Community College

BACKGROUND:The Pacific region has undergone nutrition transition. OBJECTIVES:This study aimed to examine the quadruple burden of malnutrition in children among jurisdictions of the United States-affiliated Pacific (USAP) region. METHODS:A total of 3480 children in 11 jurisdictions from the USAP region [Alaska, American Samoa, Commonwealth of the Mariana Islands (CNMI), Federated States of Micronesia (FSM), Guam, Hawai'i]. Jurisdictions were categorized according to the World Bank income categories of lower middle income (FSM), upper middle income [American Samoa, Palau, Republic of the Marshall Islands (RMI)], and high income (Hawai'i, Alaska, Guam, CNMI). The following 4 population indicators were evaluated: 1) obesity and 2) stunting using standardized measured anthropometry, 3) inadequacy, and 4) excess of dietary intake of micronutrients of concern globally (iron, zinc, and vitamin A) and in the region (vitamin D, vitamin E, calcium, niacin, folate, and sodium). Frequencies of each malnutrition form were computed. RESULTS:Across the USAP region, there were ≥10% of children with each form of malnutrition. The overall prevalence of stunting across all jurisdictions was 11.4%; varying from a low in American Samoa at 1.7% to a high in RMI at 40%. Overall prevalence of obesity was 13.6%, ranging from a low in RMI of 0% to a high in American Samoa of 25.4%. Overall prevalence of (any of the 9 studied) micronutrient inadequacies was 98.1%, driven by dietary vitamin D inadequacy (96.0%). Overall prevalence of micronutrient excess was 96.2%, driven by sodium excess (92.4%). CONCLUSIONS:There is a quadruple burden of malnutrition in the USAP. Micronutrient inadequacy and excess are the most important forms of malnutrition at 98.1% and 96.2%, respectively. Nutrition promotion should focus on healthy diets, especially in regions undergoing nutrition transition.

IntroductionIn 2014, the National Institutes of Health (NIH) invested in the Building Infrastructure Leading to Diversity (BUILD) initiative to enhance diversity in the biomedical research workforce. As one of ten grantees nationwide, the BUILD EXITO project at Portland State University established an institutionally and geographically diverse consortium including local community colleges, a research-intensive medical institution, and universities and community colleges around the Pacific Rim. The goal of this collaboration was to support comprehensive research training for undergraduates from backgrounds historically underrepresented in the biomedical workforce. This manuscript aims to provide insights into creating and sustaining a large-scale multi-institutional consortium.MethodsUsing a collaborative and reflective approach, this study presents a collective account of developing and sustaining a decade-long equity-focused partnership. The authors, all deeply involved in the partnership, participated in a series of semi-structured conversations designed to elicit strategies and lessons learned for building and sustaining multi-institutional collaborations.ResultsThree main themes arose from the reflections on core strategies for creating and maintaining the partnership: 1) having a robust framework for diverse, equitable, and inclusive partnership, 2) equitable, flexible opportunities for goal setting and program implementation, and 3) planning for sustainability from the beginning. Obstacles faced throughout the decade-long partnership include the retention of all partners and the tension between institutional buy-in and the pursuit of external funding. Finally, the Partners defined two lessons learned from the EXITO experience: 1) the importance of a critical mass of stakeholders, and 2) the need to expand institutional leadership teams for partner sustainability.DiscussionWhile working across institutional boundaries may present challenges, multi-institutional partnerships allow for a broader reach to diverse student populations and create meaningful access to opportunities that may not otherwise exist. The EXITO infrastructure serves as a model for developing and sustaining partnerships for equity-focused student programs.

Background Multiple international growth reference systems exist for classifying child undernutrition and excess weight, yet different references yield systematically different prevalence estimates. This has important implications for surveillance in Pacific Islander populations, where both CDC and WHO references are used across jurisdictions. Objective To quantify classification discrepancies between WHO Growth Standards (ages 2–5 years), WHO Growth Reference (ages 6–8 years), and CDC Growth Charts (ages 2–8 years) in Pacific Islander children, and assess implications for population health surveillance. Methods This secondary cross-sectional analysis used 2014 data from the Children's Healthy Living (CHL) Program (n = 5,499 children aged 2–8 years from 11 Pacific jurisdictions). Weight and height were measured by trained, standardized measurers. Children were classified by each reference system using SAS programs provided by WHO and CDC. Agreement was evaluated using McNemar's test, kappa coefficients, and percent agreement. Results Height-for-age agreement was high across both age groups (≥98.3%). BMI-for-age agreement differed substantially by age: poor for ages 2–5 years (kappa = 0.26; 85.5% agreement) and high for ages 6–8 years (kappa = 0.86; 97.9% agreement). For ages 2–5 years, WHO classified 11 percentage points more children as overweight than CDC. When identical percentile cutoffs were applied across reference datasets, prevalence differences narrowed substantially, indicating that most discrepancies result from differing classification criteria rather than reference population differences. Conclusions Growth reference selection introduces systematic measurement bias into Pacific Islander child health surveillance. Surveillance systems should maintain reference consistency over time, explicitly report reference criteria, and consider dual reporting to enable valid temporal and geographic comparisons. Future research should evaluate which reference better predicts health outcomes in this population. Statement of Significance This study provides the first quantification of growth reference classification discrepancies in a large, multi-jurisdiction Pacific Islander pediatric sample, demonstrating that most CDC–WHO prevalence differences result from differing classification criteria rather than true population growth differences, with direct implications for cross-jurisdictional surveillance validity.

BACKGROUND:Since diet adequacy depends in part on the quality of the local food supply, policy makers, farmers, and nutritionists need to know which foods to focus on to improve dietary adequacy and nutrition related health. OBJECTIVES:The Children's Healthy Living (CHL) Food Systems resilience project, which includes 5 United States-Affiliated Pacific (USAP) jurisdictions, developed a framework to identify "Signal Nutrients" and "Signature Foods" for food-system interventions to improve the diet and health of USAP children. METHODS:The framework identifies "Signature Foods," defined as foods consumed by the population and associated with health conditions, which can be used as leverage points to affect health and the food system. The framework was applied to 2543 CHL children aged 2-8 y using food records and anthropometric measures. The intermittent consumption of foods made direct identification of foods associated with health difficult. Therefore, the framework first identified "Signal Nutrients" associated with health conditions (overweight, obesity, and acanthosis nigricans) using logistic regression. The analysis was then repeated for Signal Nutrients sourced from specific food types and food classes to identify the food items driving nutrient associations. Foods strongly associated (standardized [Std] β: >0.025 in absolute value) with health conditions, and in the same direction as the Signal Nutrients, were designated as Signature Foods. RESULTS:The framework identified 6 Signal Nutrients and 26 Signature Foods. For example, the Signal Nutrient calcium was found to be inversely associated with obesity (P = 0.0002). Twenty-four foods that contributed to calcium intake were examined for their association with obesity. Signature Foods identified for obesity and calcium were milk (Std β: ∼0.08), dairy other than milk (Std β: 0.06), fresh fish (Std β: 0.03), and cereal (Std β: 0.11). CONCLUSIONS:Identifying strategic uses of limited resources for nutrition and health promotion can be aided by a framework that utilizes objective data sources and knowledge of community partners. Fish may be considered a potential intervention point to promote, given its importance to the USAP region and because campaigns to increase child milk consumption already exist.

Background:Multiple international growth reference systems exist for classifying child undernutrition and excess weight, yet different references yield systematically different prevalence estimates. This has important implications for surveillance in Pacific Islander populations, where both the Centers for Disease Control and Prevention (CDC) and WHO references are used across jurisdictions. Objectives:This study aimed to quantify classification discrepancies between WHO Growth Standards (ages 2-5 y), WHO Growth Reference (ages 6-8 y), and CDC Growth Charts (ages 2-8 y) in Pacific Islander children, and to assess implications for population health surveillance. Methods:This secondary cross-sectional analysis used 2014 data from the Children's Healthy Living Program (n = 5499 children aged 2-8 y from 11 Pacific jurisdictions). Weight and height were measured by trained, standardized measurers. Children were classified by each reference system using SAS programs provided by the WHO and CDC. Agreement was evaluated using McNemar's test, kappa coefficients, and percent agreement. Results:Height-for-age agreement was high across both age groups (≥98.3%). BMI-for-age agreement differed substantially by age: poor for ages 2 to 5 y (kappa = 0.26; 85.5% agreement) and high for ages 6 to 8 y (kappa = 0.86; 97.9% agreement). For ages 2 to 5 y, the WHO classified 11 percentage points more children as overweight than the CDC. When identical percentile cutoffs were applied across reference datasets, prevalence differences narrowed substantially, indicating that most discrepancies result from differing classification criteria rather than reference population differences. Conclusions:Growth reference selection introduces systematic measurement bias into Pacific Islander child health surveillance. Surveillance systems should maintain reference consistency over time, explicitly report reference criteria, and consider dual reporting to enable valid temporal and geographic comparisons. Future research should evaluate which reference better predicts health outcomes in this population.